Is text preprocessing really all that necessary for NLP?
It all depends on the quality of data. Due to old rule "Garbage in, garbage out" link
, if you have bad quality data(data redundancy, unstructured data, too much memory, etc) your results won't be spectacular. 

In other cases, everybody could be a Data Scientist, because its only task was "put raw text into classifier". Also, you should remember that BERT or GPT-2 it's deep learning algorithms so they not need too much processing. Using preprocessing in machine learning is more that needed(prediction of sentiment for example).

Shortly, preprocessing is optional, but highly advisable.